Výsledky vyhledávání - "Kimmel, Andrew"

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Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands

Autor: Wen, Bowen, Mitash, Chaitanya, Soorian, Sruthi, Kimmel, Andrew, Sintov, Avishai, Bekris, Kostas E.

Publikováno v: IEEE International Conference on Robotics and Automation (ICRA) 2020

Many manipulation tasks, such as placement or within-hand manipulation, require the object's pose relative to a robot hand. The task is difficult when the hand significantly occludes the object. It is especially hard for adaptive hands, for which it

Externí odkaz: http://arxiv.org/abs/2003.03518

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Fast, Anytime Motion Planning for Prehensile Manipulation in Clutter

Autor: Kimmel, Andrew, Shome, Rahul, Littlefield, Zakary, Bekris, Kostas

Many methods have been developed for planning the motion of robotic arms for picking and placing, ranging from local optimization to global search techniques, which are effective for sparsely placed objects. Dense clutter, however, still adversely af

Externí odkaz: http://arxiv.org/abs/1806.07465

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Fast Model Identification via Physics Engines for Data-Efficient Policy Search

Autor: Zhu, Shaojun, Kimmel, Andrew, Bekris, Kostas E., Boularias, Abdeslam

This paper presents a method for identifying mechanical parameters of robots or objects, such as their mass and friction coefficients. Key features are the use of off-the-shelf physics engines and the adaptation of a Bayesian optimization technique t

Externí odkaz: http://arxiv.org/abs/1710.08893

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Information-theoretic Model Identification and Policy Search using Physics Engines with Application to Robotic Manipulation

Autor: Zhu, Shaojun, Kimmel, Andrew, Boularias, Abdeslam

We consider the problem of a robot learning the mechanical properties of objects through physical interaction with the object, and introduce a practical, data-efficient approach for identifying the motion models of these objects. The proposed method

Externí odkaz: http://arxiv.org/abs/1703.07822

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Autor: Krontiris, Athanasios, Shome, Rahul, Dobson, Andrew, Kimmel, Andrew, Yochelson, Issac, Bekris, Kostas

This work proposes a method for effectively computing manipulation paths to rearrange similar objects in a cluttered space. The solution can be used to place similar products in a factory floor in a desirable arrangement or for retrieving a particula

Externí odkaz: http://arxiv.org/abs/1404.6573

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